Wait time is the worst
I can hardly sit
No one has the time
Someone is always late
--The Strokes, Call Me Back (2011)The callback system in Matplotlib is central to its interactivity. Unless you are working with the interactive plotting mode on, execution of the script stops when plt.show() is called. Without the ability to execute any additional code, the only way to program interactivity is to register actions to be taken upon some event such as a button click, mouse cursor motion, or key press. Matplotlib's callback system has a base set of events and many callbacks that we have already discussed, such as the default keymap discussed in the previous chapter and the ability to pan a plot. Furthermore, it is possible to add new kinds of events, giving the developer full access to Matplotlib's cross-platform callback system.
The callback system is figure-oriented. Any GUI action that can trigger a callback can only happen to whichever figure window is currently in focus. There are no global actions that can trigger callbacks across multiple figures. The callback function will get an Event object that contains pertinent information about the fired event. In the following example, we will hook up two events to a figure: a keyboard button press and a mouse button press. There are two callback functions, each printing out some of the available pieces of information for their respective events:
Code: chp2/basic_mpl_connect.py
from __future__ import print_function
import matplotlib.pyplot as plt
def process_key(event):
print("Key:", event.key)
def process_button(event):
print("Button:", event.x, event.y, event.xdata, event.ydata, event.button)
fig, ax = plt.subplots(1, 1)
fig.canvas.mpl_connect('key_press_event', process_key)
fig.canvas.mpl_connect...
What is the purpose of interactive plotting? Why is it important for Matplotlib to provide this feature? It is important because you want to interact with your data. What you plot in the figure is a visual representation of your data, and giving it interactivity brings that data an extra step closer to the real world by providing your users the means to interact with that data in a more physically intuitive manner. It is all about data exploration.
So far, for our project, we have only developed the means to display our storm and radar data. While we could simply use these viewers and then manually edit the associated shapefile, it would not be practical. We should be able to provide users the means to interrogate their data. To do this, we will use pick_event to add the ability to select and deselect some tracks. As a simple example, we will make a track thicker when it is selected and make it thinner when it is deselected (or simply, selected again). Let's build upon...
Try the previous radar example again. This time, go forward a few frames and then zoom in with the zoom tool. Now go back a frame.
Go ahead, I'll wait.
Surprised? Remember that Matplotlib has its own built-in keymap. In the default keymap, the left arrow means to go back to a previous view. When we zoomed in and then pressed the left arrow key, not only did we go back a frame via our callback, but we also went back to the original view prior to zooming via Matplotlib's default keymap. The default keymap is a very important and useful feature for providing basic interactivity for most users. However, when developing your own application using Matplotlib, you might want to disable Matplotlib's keymap entirely. The following example shows how to do that while demonstrating the next important feature of the callback system: disconnecting a callback. In this example, you can now press any non-system key or combination of keys without ever triggering...
We can see that our application is going to grow in complexity very soon add we continue to add features. Our current manner of keymapping is probably not going to be easily maintainable as the number of actions increase. Let's take a moment to implement something better. The most essential feature of a keymap is to tie a predefined action to an arbitrary key or key combination. This seems like the perfect job for a dictionary. Furthermore, as the keymap grows, it will become important to be able to display the keymap in a helpful manner to your users. Each key/action pair will need to come with a description that can later be displayed on demand. Also, keeping in mind that our ControlSys class is likely to grow in complexity soon, let's implement this keymap feature as a separate class that ControlSys will inherit. The code is as follows:
Source: chp2/stormcell_anim_with_keymap.py
class KeymapControl:
def __init__(self, fig):
self.fig = fig
# Deactivate...
We demonstrated pick events earlier, showing how to select a storm track, changing its thickness, but we haven't incorporated picking into our current design yet. Much in the same vein as the KeymapControl class, let's create a PickControl class that will keep a list of pick functions (pickers) and manage their connection to the callback system for us:
Source: chp2/select_stormcells.py
class PickControl:
def __init__(self, fig):
self.fig = fig
self._pickers = []
self._pickcids = []
def connect_picks(self):
for i, picker in enumerate(self._pickers):
if self._pickcids[i] is None:
cid = self.fig.canvas.mpl_connect('pick_event', picker)
self._pickcids[i] = cid
def disconnect_picks(self):
for i, cid in enumerate(self._pickcids):
if cid is not None:
self.fig.canvas.mpl_disconnect(cid)
self._pickcids[i] = None
def add_pick_action...
The callback system is figure-oriented. Any GUI action that can trigger a callback can only happen to whichever figure window is currently in focus. There are no global actions that can trigger callbacks across multiple figures. The callback function will get an Event object that contains pertinent information about the fired event. In the following example, we will hook up two events to a figure: a keyboard button press and a mouse button press. There are two callback functions, each printing out some of the available pieces of information for their respective events:
Code: chp2/basic_mpl_connect.py
from __future__ import print_function
import matplotlib.pyplot as plt
def process_key(event):
print("Key:", event.key)
def process_button(event):
print("Button:", event.x, event.y, event.xdata, event.ydata, event.button)
fig, ax = plt.subplots(1, 1)
fig.canvas.mpl_connect('key_press_event', process_key)
fig.canvas.mpl_connect('button_press_event', process_button...
What is the purpose of interactive plotting? Why is it important for Matplotlib to provide this feature? It is important because you want to interact with your data. What you plot in the figure is a visual representation of your data, and giving it interactivity brings that data an extra step closer to the real world by providing your users the means to interact with that data in a more physically intuitive manner. It is all about data exploration.
So far, for our project, we have only developed the means to display our storm and radar data. While we could simply use these viewers and then manually edit the associated shapefile, it would not be practical. We should be able to provide users the means to interrogate their data. To do this, we will use pick_event to add the ability to select and deselect some tracks. As a simple example, we will make a track thicker when it is selected and make it thinner when it is deselected (or simply, selected again). Let's build upon the track...
Try the previous radar example again. This time, go forward a few frames and then zoom in with the zoom tool. Now go back a frame.
Go ahead, I'll wait.
Surprised? Remember that Matplotlib has its own built-in keymap. In the default keymap, the left arrow means to go back to a previous view. When we zoomed in and then pressed the left arrow key, not only did we go back a frame via our callback, but we also went back to the original view prior to zooming via Matplotlib's default keymap. The default keymap is a very important and useful feature for providing basic interactivity for most users. However, when developing your own application using Matplotlib, you might want to disable Matplotlib's keymap entirely. The following example shows how to do that while demonstrating the next important feature of the callback system: disconnecting a callback. In this example, you can now press any non-system key or combination of keys without ever triggering a built...
We can see that our application is going to grow in complexity very soon add we continue to add features. Our current manner of keymapping is probably not going to be easily maintainable as the number of actions increase. Let's take a moment to implement something better. The most essential feature of a keymap is to tie a predefined action to an arbitrary key or key combination. This seems like the perfect job for a dictionary. Furthermore, as the keymap grows, it will become important to be able to display the keymap in a helpful manner to your users. Each key/action pair will need to come with a description that can later be displayed on demand. Also, keeping in mind that our ControlSys class is likely to grow in complexity soon, let's implement this keymap feature as a separate class that ControlSys will inherit. The code is as follows:
Source: chp2/stormcell_anim_with_keymap.py
class KeymapControl:
def __init__(self, fig):
self.fig = fig
# Deactivate the... Description
This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.
Who is this book for?This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.
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(Includes tracking information) Product DetailsPublication date, Length, Edition, Language, ISBN-13
Publication date : Mar 24, 2015
Length: 174 pages
Edition : 1st
Language : English
ISBN-13 : 9781783988846
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Estimated delivery fee Deliver to United StatesEconomy delivery 10 - 13 business days
Free $6.95
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$21.95
(Includes tracking information) Product DetailsPublication date : Mar 24, 2015
Length: 174 pages
Edition : 1st
Language : English
ISBN-13 : 9781783988846
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Sanjay Mishra Dec 30, 2019
If you need to quickly produce graphs and charts and explore data, this is the book for you.You could possibly get the same information from user manuals, blog posts and such like given enough time, but this book makes it easy to grasp the information and be quickly productive.
Amazon Verified reviewJuan Nunez-Iglesias Apr 03, 2018
I highly recommend Ben's book. I fumbled around for a long time with minor interactive matplotlib features. Then I read his book and it completely clarified my mental model of mpl interactivity and, indeed, of GUIs in general.Here's an excerpt that describes my story quite well:"""Indeed, given that the primary audience for Matplotlib is scientific programmers for whom GUIs are, at best, an afterthought, Matplotlib provides a gradual curve to create full-fledged GUI applications. For simple GUI tasks, one can go quite far with Matplotlib without ever having to adopt a GUI platform. And, as we will see in the next chapter, taking those final steps into a GUI application would not require getting rid of any existing code."""If you're a scientist looking to add a bit of interactivity to your data, or to move from a purely command-line interface to providing some graphical interactivity and control, this is a fantastic book to start with. Even if you end up using some newer frameworks such as Bokeh, the ideas in this book about GUI loops and callbacks will be useful forever.
Amazon Verified reviewDr. Andrew G. Meigs Feb 04, 2016
Good book, but a bit short. Nice tidbits throughout.
Amazon Verified reviewPhu ta Feb 18, 2016
I think the overall content is okay, good for beginners who want to learned to develop interactive Python app. Keep in mind that specifically builds up a weather application in Matplotlib. So depend on your interest, it may or may not be helpful.
Amazon Verified reviewPhilip H Sep 15, 2018
A few pages on plotting; the rest of the book is junk. I would ask for my money back if I could!
Amazon Verified review FAQsWhen you buy any Print edition of our Books, you can redeem (for free) the eBook edition of the Print Book you’ve purchased. This gives you instant access to your book when you make an order via PDF, EPUB or our online Reader experience.
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